Virtually every organic compound, including lipoproteins and apolipoproteins, has a near-IR spectrum that distinguishes it from other compounds. Near-IR spectrometry can be employed profitably in the analysis of serum lipoproteins and cholesterol. Cholesterol is carried in a wide variety of lipoprotein particles, including high-density lipoprotein (HDL) and low-density lipoprotein (LDL) particles. Accurate analysis of serum cholesterol is essential for identification of individuals at risk for arteriosclerotic cardiovascular disease and for implementation of effective therapeutic regimens. Conventional analytical approaches allow discrimination between total cholesterol and the principal forms in which cholesterol is transported in the blood, HDL and LDL. However, these methods are limited on several accounts. First, in many laboratories the analytical methods are fraught with error; it has been reported that up to 33% of the reported HDL values are inaccurate. Second, exceedingly wide interassay variability has prompted some investigators to suggest that up to ten replicate analyses may be necessary to obtain a meaningful result. Finally, the conventional methods provide no information about apolipoproteins (A-I, A-II, B-100) which have been touted as more sensitive predictors of cardiovascular risk than either cholesterol, HDL or LDL. Against this background, we now propose a rapid, novel method of serum lipoprotein determination based on near-IR spectrometry with the potential to increase the accuracy of cholesterol measurement, to permit determination of apolipoproteins along with HDL and LDL, and to dramatically improve the cost-effectiveness of strategies for widespread cholesterol screening. This proposal will test the following hypotheses: (1) that near-IR spectrometry is capable of differentiating among cholesterol, HDL, LDL, and apolipoproteins A-I, A-II, and B in human sera, and capable of quantifying these analytes rapidly and simultaneously, (2) that a new parallel supercomputer method provides more accurate analyses than existing pattern- recognition techniques, (3) that orbital asymmetry in calibration leads to misidentified samples that must be reclassified to achieve adequate spectral assimilation and accurate multicomponent serum analysis (4) that the near-IR/parallel computer method provides accurate assays of lipoproteins and apolipoproteins in whole blood as well as serum (5) that hyphenation of near-IR and acoustic-resonance spectrometries yields improved analyses of lipoproteins and apolipoproteins with fewer misclassified samples.